POS0387 RISK STRATIFICATION APPROACHES PERFORM DIFFERENTLY IN SSc-ASSOCIATED PAH IN EUSTAR
Authors: H. J. Bjørkekjær, C. Bruni, P. Carreira, P. Airò, C. P. Simeón-Aznar, M. E. Truchetet, A. Giollo, A. Balbir-Gurman, M. Martin, C. P. Denton, A. Gabrielli, H. Fretheim, I. Barua, H. Bitter, Ø. Midtvedt, K. Broch, A. Andreassen, Y. Tanaka, G. Riemekasten, U. Müller-Ladner, M. Matucci-Cerinic, I. Castellví, E. Siegert, E. Hachulla, O. Distler, A. M. Hoffmann-Vold
Journal: Annals of the Rheumatic Diseases (2022)

Background Pulmonary arterial hypertension (PAH) is a major clinical challenge in systemic sclerosis (SSc), and is associated with high mortality. Risk stratification provides an estimate for individual patient risk of 1-year mortality. The aim is to detect patients with the worst prognosis to optimize management strategies. Nine risk stratification approaches have been proposed in PAH, but have not been validated in SSc-PAH. Objectives To assess four risk stratification models and their performance to predict 1- and 3- year mortality and to identify the best risk assessment approach for SSc-PAH. Methods We included all patients with SSc diagnosed with PAH by right heart catheterization (RHC) from the European scleroderma trial and research (EUSTAR) database from 2001 to February 2021. PAH was defined as mean pulmonary arterial pressure (mPAP) ≥25 mmHg, pulmonary artery wedge pressure (PAWP) ≤15mmHg, and pulmonary vascular resistance (PVR) &gt;3 Wood units (WU) in the absence of significant interstitial lung disease. We applied four different approaches for risk stratification at time of PAH diagnosis. Risk parameters included New York Heart Association (NYHA) class, 6-minute walk distance (6MWD), NT-proBNP or BNP, and echocardiographic and hemodynamic parameters with cut-off values based on the 2015 ESC/ERS Guidelines. Model 1 and 2 stratified patients into low, intermediate and high-risk categories; while Model 3 and 4 stratified the patients into four categories (low, intermediate-low, intermediate-high and high). Model 1: Patients with ≥ 1 high-risk parameter were considered at high risk; with ≥ 1 intermediate-risk parameter at intermediate risk, otherwise at low risk 1 Model 2: Each variable was graded from 1 to 3 representing low to high risk. The mean of available risk parameters was rounded to the nearest integer to define the risk category 2 Model 3: Equals Model 2, but the intermediate risk group was divided into intermediate-low and intermediate-high based on the mean score 3 Model 4: Stratifies patients into four risk categories based on the proportion of low-risk parameters 3 We performed analysis of 1- and 3- year mortality in patients with a minimum follow-up of 1 and 3 years, respectively. Results Of 911 patients who conducted RHC, 273 (30%) were diagnosed with SSc-PAH according to the inclusion criteria (Table 1). Median follow-up time was 2.8 years (IQR 1.3-5.3). The models varied in their ability to predict mortality (Figure 1). Model 1 and 4 either over- or underestimated mortality. Model 2 stratified patients according to the expected 1-year mortality of &lt;5%, 5-10% and &gt;10% suggested by the ESC/ERS Guidelines. Model 3, which divided the intermediate risk group in two different risk groups, segregated the risk of mortality further within this group. Table 1. Demographic and clinical characteristics of patients segregated by risk stratification (Model 3) N All patients (n=273) Low-risk (n=78) Intermediate-low (n=118) Intermediate-high (n=56) High-risk (n=21) Age, years (SD ) 273 65 (10.7) 65 (10.3) 65 (10.7) 65 (10.8) 67 (12.8) Female sex, n (% ) 273 230 (84) 64 (82) 98 (83) 48 (86) 20 (95) lcSSc, n (% ) 263 221 (84) 60 (80) 99 (86) 47 (90) 15 (71) NYHA 3 or 4, n (% ) 261 155 (59) 12 (16) 75 (68) 49 (89) 19 (95) NT-proBNP, pg/ml (IQR ) 111 1941 (230-1485) 215 (103-377) 763 (325-1418) 1926 (1051-5681) 3314 (1129-6553) 6MWD, m (SD ) 196 321 (124.1) 404 (119.7) 314 (99.9) 262 (128.6) 215 (96.0) RHC: - mPAP, mmHg (SD ) 273 40 (11.0) 35 (8.8) 41 (11.5) 41 (10.8) 45 (11.6) - PAWP, mmHg (SD ) 273 9 (3.2) 9 (3.0) 9 (3.4) 9 (3.2) 8 (3.1) - Cardiac index, l/min/m 2 (SD ) 260 2.8 (0.8) 3.2 (0.7) 2.7 (0.8) 2.6 (1.0) 2.0 (0.5) - PVR, WU (SD ) 273 7.4 (4.1) 5.3 (2.8) 7.9 (4.0) 7.9 (4.2) 11.3 (4.7) Figure 1. 1- and 3-year mortality according to risk category in the four different models Conclusion Model 3 provides signals for a better risk stratification of patients with newly diagnosed SSc-PAH, with progressively increasing mortality across the categories. This may provide guidance for optimized management in clinical practice. References [1]Hoffmann-Vold, Rheum 2018 [2]Kylhammar, Eur Heart J 2018 [3]Kylhammar, ERJ open 2021 Acknowledgements The authors thank all EUSTAR collaborators. Disclosure of Interests Hilde Jenssen Bjørkekjær: None declared, Cosimo Bruni Speakers bureau: Actelion, Consultant of: Boehringer-Ingelheim, Patricia Carreira: None declared, Paolo Airò Speakers bureau: Boehringer Ingelheim, Bristol-Myers-Squibb, Consultant of: Bristol-Myers-Squibb, Grant/research support from: Bristol-Myers-Squibb, Roche, Janssen, CSL Behring, Carmen Pilar Simeón-Aznar Speakers bureau: Janssen, Boehringer Ingelheim and MSD, Consultant of: Janssen, Boehringer Ingelheim, Marie-Elise Truchetet: None declared, Alessandro Giollo: None declared, Alexandra Balbir-Gurman: None declared, Mickael Martin: None declared, Christopher P Denton Speakers bureau: Boehringer Ingelheim; Janssen, Consultant of: Boehringer Ingelheim; GSK; Corbus; Sanofi; Roche; Horizon; CSL Behring; Acceleron, Grant/research support from: CSL Behring; Horizon; GSK; Servier, Armando Gabrielli: None declared, Håvard Fretheim Consultant of: Bayer, GSK, Actelion, Imon Barua: None declared, Helle Bitter Speakers bureau: Boehringer Ingelheim, Øyvind Midtvedt: None declared, Kaspar Broch: None declared, Arne Andreassen: None declared, Yoshiya Tanaka Speakers bureau: Gilead, Abbvie, Behringer-Ingelheim, Eli Lilly, Mitsubishi-Tanabe, Chugai, Amgen, YL Biologics, Eisai, Astellas, Bristol-Myers, Astra-Zeneca, Consultant of: Eli Lilly, Daiichi-Sankyo, Taisho, Ayumi, Sanofi, GSK, Abbvie, Grant/research support from: Asahi-Kasei, Abbvie, Chugai, Mitsubishi-Tanabe, Eisai, Takeda, Corrona, Daiichi-Sankyo, Kowa, Behringer-Ingelheim, Gabriela Riemekasten: None declared, Ulf Müller-Ladner: None declared, Marco Matucci-Cerinic: None declared, Ivan Castellví: None declared, Elise Siegert: None declared, Eric Hachulla Speakers bureau: Johnson &amp; Johnson, GlaxoSmithKline, Roche-Chugai, Consultant of: Bayer, Boehringer Ingelheim, GlaxoSmithKline, Johnson &amp; Johnson, Roche-Chugai, Sanofi-Genzyme, Grant/research support from: CSL Behring, GlaxoSmithKline, Johnson &amp; Johnson, Roche-Chugai, Sanofi-Genzyme, Oliver Distler Speakers bureau: Bayer, Boehringer Ingelheim, Janssen, Medscape, Consultant of: Abbvie, Acceleron, Alcimed, Amgen, AnaMar, Arxx, AstraZeneca, Baecon, Blade, Bayer, Boehringer Ingelheim, Corbus, CSL Behring, 4P Science, Galapagos, Glenmark, Horizon, Inventiva, Kymera, Lupin, Miltenyi Biotec, Mitsubishi Tanabe, MSD, Novartis, Prometheus, Roivant, Sanofi and Topadur, Grant/research support from: Kymera, Mitsubishi Tanabe, Boehringer Ingelheim, Anna-Maria Hoffmann-Vold Speakers bureau: Actelion, Boehringer Ingelheim, Jansen, Lilly, Medscape, Merck Sharp &amp; Dohme, Roche, Consultant of: Actelion, ARXX, Bayer, Boehringer Ingelheim, Jansen, Lilly, Medscape, Merck Sharp &amp; Dohme, Roche, Grant/research support from: Boehringer Ingelheim